Gas Recognition Research Articles

A Gas Recognition Method based on Hough Transform and K-Means Algorithm

A Gas Recognition Method based on Hough Transform and K-Means Algorithm

Fuzzy Logic Applications In Chemical Processes

Fuzzy logic a new approach was intended to emulate human reasoning using calculations and operations with fuzzy groups and linguistic variables. Fuzzy variables describe qualitative expressions such as very slow, slow, fast, very fast, and so on. The application of fuzzy logic techniques has been increasing rapidly in the last few years. Fuzzy logic is used in target tracking, pattern recognition, robotics, power systems, controller design, chemical engineering, biomedical engineering, vehicular technology, economy management and decision making, aerospace applications, communications and networking, electronic engineering, and civil engineering. In many chemical engineering systems, the classification of product quality characteristics is performed by human experts, due to the absence of measuring devices. The development of mathematical models for such systems is a rather difficult task, since no equations based on first principles can be written. Chemical engineering has employed fuzzy logic in the detection of chemical agents as well as gas recognition. It has also been applied to processes control, batch distillation column, separation process, and kinetics. In this research, we investigate these applications in more detail.

Optical and morphological characterization of bispyrazole thin films for gas sensing applications

The optical gas recognition capabilities of thin film layer of 4-[bis[(3,5-dimethyl-1H-pyrazol-1-yl)methyl]-amino]phenol deposed on quartz substrates were studied. The dynamic gas responses to the following analytes have been investigated as air pollutants (SO2, NO2, CO, CH4 and NH3). The spin-coated bispyrazole layer appears to have reversible response towards SO2 and a very low and irreversible response to NO2. The selectivity of the thin film based on bispyrazole layer with respect to other analytes was also examined and the present data show that the thin sensing layer in the presence of CO, CH4 and NH3 in low concentration does not influence its optical properties.

Gas Analysis by Monitoring Molecular Diffusion in a Microfluidic Channel

Despite the increasing industrial and domestic demand for gas analyzers, the unmanageable size and cost of the available devices prevent them from fulfilling this pervasive need. In this paper, we demonstrate that, monitored by a generic gas sensor, the progress rate of a gaseous analyte's free diffusion through an air-filled centimeter-long microfluidic channel yields sufficient information for gas recognition. The installation of additional channels made from different materials provides more uncorrelated information, enabling more detailed gas analyses. This device classifies gases based on their physical features at room temperature, namely, diffusivity and interaction (physisorption/desorption) with channel walls. This process does not degrade the gas discriminating element of the instrument. Our prototype, featuring a 50 mm long 50 μm bore borosilicate glass channel, successfully differentiated between 24 analytes, including four butanol isomers, and estimated the compositions of their binary and ternary gas mixtures dispersed in air at different concentration levels. The findings presented here are directly applicable to the production of a new inexpensive, compact, portable, and durable generation of artificial olfaction system whose performance is almost entirely independent of the utilized gas sensor's drift.

Development of a portable electronic nose based on chemical surface acoustic wave array with multiplexed oscillator and readout electronics

A portable electronic nose (E-nose) based on a novel chemical surface acoustic wave array with multiplexed oscillator and readout electronics was developed and tested. The sensor array was fabricated on a large K 2 128° YX-LiNbO 3 sensing substrate. On the surface of this substrate, an interdigital transducer (IDT) was made with a Cr/Au film as a metallic structure. The center frequency of the sensing chips was designed at 99.8 MHz. Seven polymers, poly-4-vinylphenol (P4VP), poly-vinylacetate (PVAc), poly-N-vinylpyrrolidone (PNVP), polyethyleneglycol (PEG), polystyrene (PS), polystyrene-co-maleic anhydride (PSMA), and polysulfone (PSu), were coated on the sensing area of Au surface between the center of the IDTs. The 2 × 2 non-continuous SAW array could be controlled by a multiplexing technique and sensor signals could be obtained by readout electronics with an 89C51 microprocessor. Five different organic vapors were adopted as samples to test the developed system. The frequency shifts (Δ f) were measured and the stable state was about 1 kHz. Two-way hierarchical clustering analysis was used to analyze the measured data. It showed that based on the analysis method, gases and polymers with similar chemical properties were grouped into the same family. The results suggest that the development of a portable E-nose and the applied analysis method are promising for practical applications of gas detection and recognition.

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Chemiresistor sensors array optimization by using the method of coupled statistical techniques and its application as an electronic nose for some organic vapors recognition

An electronic nose (EN) based on an array of chemiresistors, combined with a preconcentrator unit, for the detection of some volatile organic vapors was developed. In order to choose the proper polymers, seven potential polymers were chosen from numerous available polymers according to the principle of the linear solvation energy relationship (LSER). Different possible sensors arrays (128 arrays) composed of these seven polymers were designed by full factorial design (FFD). Principal component analysis (PCA) showed that four of seven polymers had enough ability to recognize different gas classes. By using Hierarchical cluster analysis (HCA), the tested polymers were categorized into four main groups with respect to their recognition ability. Combination of the FFD with PCA and HCA, brought to the identification of 8 proper arrays containing four polymers in each array. Precisely evaluation of predicted arrays with respect to their calculated resolution factors showed that the electronic nose containing the polymers of 75% pheny125% methylpolysiloxane (OV25), hexafluoro-2-propanolsubstituted polysiloxane (SXFA), poly bis(cyanopropyl)-siloxane (SXCN) and poly(ethylene maleate) (PEM) was the most proper design for recognition of analytes of interest. The fabricated EN was used successively for target gas recognition at three different concentrations.

Extracting discriminative information from the Padé-Z-transformed responses of a temperature-modulated chemoresistive sensor for gas recognition

The response patterns of a temperature-modulated chemoresistive gas sensor were transformed to multi-exponential functions which facilitated the extraction of their discriminative features for gas diagnosis. The patterns were generated for air contaminated with different concentrations of various volatile organic compounds by applying a staircase heating voltage waveform to the microheater of a tin oxide-based sensor that modulated its operating temperature in the 50–400 °C range. Padé-Z transform was utilized for the transformation, and a novel heuristic procedure facilitated the extraction of the components of the feature vectors from the transformed data. These vectors were classified by the available techniques. The method differentiated the patterns generated for methanol, ethanol, 1-propanol, 1-butanol, and acetone contaminations in the wide concentration range examined. The method was also used to separately estimate the amount of the discriminative information in various steady state and transient response features; the results are anticipated to help design more elaborate temperature-modulated sensors for gas diagnosis.

Characterization of Integrated Tin Oxide Gas Sensors With Metal Additives and Ion Implantations

Post-treatment of the sensing film in tin oxide gas sensor arrays is widely used to improve the selectivity in gas recognition applications. This letter describes the characterization study of an integrated tin oxide gas sensor array chip in which the sensing films are modified using metal additives and ion implantations. Measurement results reveal that metal additives present a higher impact on the sensor sensitivity compared with ion implantations. The latter has no significant effect on the sensing properties. The drift is increased for the sensors with only ion implantation compared with the ones with metal additives. An array combining both post-treatment techniques is expected to improve the overall recognition performance.

A Robust and Low‐Complexity Gas Recognition Technique for On‐Chip Tin‐Oxide Gas Sensor Array

Gas recognition is a new emerging research area with many civil, military, and industrial applications. The success of any gas recognition system depends on its computational complexity and its robustness. In this work, we propose a new low‐complexity recognition method which is tested and successfully validated for tin‐oxide gas sensor array chip. The recognition system is based on a vector angle similarity measure between the query gas and the representatives of the different gas classes. The latter are obtained using a clustering algorithm based on the same measure within the training data set. Experimented results on our in‐house gas sensors array show more than 98% of correct recognition. The robustness of the proposed method is tested by recognizing gas measurements with simulated drift. Less than 1% of performance degradation is noted at the worst case scenario which represents a significant improvement when compared to the current state‐of‐the‐art.

A bio-sniffer stick with FALDH (formaldehyde dehydrogenase) for convenient analysis of gaseous formaldehyde

Abstract A stick type biochemical gas sensor (bio-sniffer) with formaldehyde dehydrogenase (FALDH) was developed for convenient analysis of gaseous formaldehyde with high gas selectivity. The bio-sniffer for formaldehyde in the gas phase was constructed by immobilizing enzyme to a Pt electrode-coated hydrophilic PTFE membrane. The oxidation current of NADH produced by the FALDH enzymatic reactions was measured by amperometric analysis. The calibration ranges of the bio-sniffer for formaldehyde in the gas phase was from 40 to 3000 ppb, which encountered the maximum permissible concentration of formaldehyde vapor in the residential house (80 ppb) and formaldehyde detection limit for the human sense of smell (410 ppb). The FALDH immobilized sniffer indicated good gas selectivity based on the substrate specificity of FALDH as gas recognition material. As the results of the environmental application, the bio-sniffer was possible to measure the formaldehyde concentration from a building timber as an exterior frame material. The calculated concentration value by a regression analysis was consistent with those of a commercially available gas sensor and a gas detector tube for formaldehyde.

New normalization procedure to improve signal pattern discrimination power in case of different concentration dependencies of the gas sensors in an array

Sample recognition with a metal oxide gas sensor array is often affected by a signal pattern dependence on the gas concentration, that blurs the class representation. The reason are differences of the sensor elements in the exponent of the power law that governs the concentration dependence of signals of the array elements. Under the power law the standard pattern normalization procedure using signal ratios eliminates the concentration dependence only if the two signals have the same power law exponent. A simple signal preprocessing algorithm is presented, which is able to suppress the differences in the non-linear concentration dependence of the array elements whereby concentration independent signal patterns can be obtained. Thereby the resolution of the pattern discrimination can be significantly improved resulting in improved gas recognition appropriate for a broad concentration range.

STW gas sensors using plasma-polymerized allylamine

Gas sensors generally consist of two major components: a gas recognition element which provides the specificity and selectivity of the measurement and a physical transducer which translates the gas absorption or desorption event into electronic signal. In this paper, plasma polymerized allylamine (PPAa) film is used as a gas recognition element and a surface transverse wave (STW) device is used as a physical transducer. It is confirmed that STW sensor devices coated with PPAa films provide high sensitivity for moisture. The STW sensor device with a 63 nm PPAa film provided twenty four times higher sensitivity than that of a non-coated STW device. In addition, the chemical structure of PPAa films is characterized by the FT-IR and the contact angle measurement.

Gas Recognition Films Fabricated by Microplasma Technology

We developed a novel fabrication method of on-demand polymer film synthesis onto a substrate under atmospheric pressure using microplasma polymerization with a laboratory-made torch-type microplasma polymerization apparatus. We used styrene as model monomer for selection of polymerization condition of microplasma-polymerization and evaluation of microplasma-polymerized (MPP-) styrene films. These films were characterized using data FT-IR, EDX, contact angle, and gas sorption property using QCM technique. Characterization results of FT-IR, contact angle, and EDX suggest that MPP-styrene films were oxidized. Results showed that gas sorption properties of MPP-styrene films were controllable by polymerization parameters of VHF power or concentration of monomer gas.

Preparation of long-lifetime gas recognition films by plasma polymerization technique

Gas sorption and desorption properties of plasma-polymerized acrylic acid film (PPAAF) and cast poly(acrylic acid) film (CPAAF) were determined by QCM technique. The gas sorption properties of PPAAF are almost the same as those of CPAAF. PPAAF showed an excellent stability in repeated usage of the gas sorption and desorption cycles.

Bio-sniffer sticks for breath analysis after drinking

Stick-type biochemical gas sensors (bio-sniffer) with alcohol oxidase (AOD) and aldehyde dehydrogenase (ALDH) were developed for convenient analysis of breath ethanol and acetaldehyde, respectively. The sniffer sticks for ethanol and acetaldehyde in the gas phase were constructed by immobilizing enzyme to electrode coated filter paper and hydrophilic PTFE membrane, respectively. The oxidation currents of hydrogen peroxide and NADH, produced by the AOD and ALDH enzymatic reactions, were measured by amperometric analysis. The calibration ranges of the biosensor for ethanol and acetaldehyde in the liquid phase were from 0.05 to 1.41 mmol/l and 1.0 to 250 μmol/l, respectively. And both sniffer sticks were used to measure ethanol and acetaldehyde vapor encountered in breath air after alcohol consumption. Each of the bio-sniffers indicated good gas selectivity based on the substrate specificity of AOD and ALDH as gas recognition material. As the results of the physiological application, the bio-sniffers were possible to measure the concentration changes in breath ethanol and acetaldehyde after drinking. The concentration values of breath ethanol and acetaldehyde obtained by the sniffers were also consistent with those of commercially available gas detector tubes for ethanol and acetaldehyde.

Characterization, Optical Recognition Behavior, Sensitivity, and Selectivity of Silica Surfaces Functionalized with a Porphyrin Monolayer

The optical gas recognition capability of a covalently self-assembled monolayer of 5,10,15-tri-{p-dodecanoxyphenyl}-20-(p-hydroxyphenyl) porphyrin molecules on silica substrates was studied. The following analytes have been investigated: NO2, CO, CH4, H2, NH3, HCl, CHCl3, C2H5OH, CH3OH, pyridine, tetrahydrofurane, triethylamine, and dimethylformamide. The self-assembled porphyrin monolayer appears highly sensitive to 1 ppm of NO2 in both anhydrous and humid conditions. The selectivity of the self-assembled porphyrin monolayer with respect to other analytes was also examined and present data show that the presence of CO, CH4, H2, and NH3 does not influence its UV−vis spectrum. Many common solvents slowly affect the position of the Soret band. The presence of HCl vapors results in a broad band extending over the entire 440−500 nm range while the starting Soret disappears. UV−vis measurements on a n-hexane 1.0·10-5 solution of the 2,3,7,8,12,13,17,18-octaethyl-21H,23H-porphine, that does not contain phenyl substituents in the meso positions, show no changes in the optical spectrum upon NO2 interaction. It emerges that aromatic substituents in the meso positions play a crucial role in determining the optical sensing properties.

「スマートマテリアル」 ＶＯＣ計測のためのホルムアルデヒドガス用酵素電極

An enzymatic gas sensor (called “bio-sniffer”) for formaldehyde vapor was constructed by immobilizing formaldehyde dehydrogenase (FALDH) to hydrophilic polytetrafluoroethylene (H-PTFE) membrane with Platinum-coated electrodes. The platinum electrodes (300 nm) were formed by sputter deposition onto both sides of the H-PTFE membrane (thickness=80 μm, pore size=0.2 μm). The oxidation current of NADH (reduction form) being produced by FALDH enzyme reaction with NAD+ (oxidized form) could be measured by amperometric analysis between two Pt electrodes. The bio-sniffer was used to measure formaldehyde vapor with the calibration range from 40 to 3000 ppb, including the maximum permitted concentration of 80 ppb, with high selectivity being attributable to the substrate specificity of FALDH as gas recognition material. By applying the FALDH sniffer for formaldehyde vapor from building timbers, the bio-sniffer could evaluate the concentration of formaldehyde, thus being in agreement with the results in the commercial available detector tube. The bio-sniffer with high gas selectivity would be effective and convenient non-invasive approach to evaluate the formaldehyde concentration in the gas phase.

Ethanol sniffing sensor with alcohol oxidase as gas recognition material

An alcohol oxidase (AOD) enzyme immobilized gas-sensor (bio-sniffer) with stick-type configuration was developed for convenient analysis of ethanol vapor. The stick-type sniffer device was constructed in a sandwich configuration with a filter paper placed between carbon- and Ag/AgCl electrodes. The electrode-coated paper was shaped by knife into 2mm-wide stick. In order to isolate a sensitive- (length: 5 mm) and terminal-areas, an epoxy-resin adhesive was applied to the middle part of the narrow stick paper. AOD was immobilized to the sensitive area with photocrosslinkable polymer. The characteristics of the stick-type sniffer moistened with phosphate buffer were assessed using standard ethanol vapor supplied from a gas generator. The oxidation current of hydrogen peroxide, produced by the AOD enzymatic reaction by applying ethanol vapor, was detected a computer-controlled potentiostat at a fixed voltage of +900 mV. The calibration range of the ethanol sniffer covered the concentration range encountered in breath after alcohol consumption including the permissible legal limit (130 ppm) for driving, and the sensing range of smell in humans. As the physiological application, the bio-sniffer was used to monitor the concentration change of breath ethanol after drinking.

Bioelectronic sniffers for ethanol and acetaldehyde in breath air after drinking

Two kinds of bioelectronic gas sensors (bio-sniffer) incorporating alcohol oxidase (AOD) and aldehyde dehydrogenase (ALDH) were developed for the convenient analysis of ethanol and acetaldehyde in expired gas, respectively. The sniffer devices for gaseous ethanol and acetaldehyde were constructed by immobilizing enzyme on electrodes covered with filter paper and hydrophilic PTFE membrane, respectively. The AOD and ALDH sniffers were used in the gas phase to measure ethanol vapor from 1.0 to 500 ppm, and acetaldehyde from 0.11 to 10 ppm covering the concentration range encountered in breath after alcohol consumption. Both bio-sniffers displayed good gas selectivity which was attributed to the substrate specificity of the relevant enzymes (AOD and ALDH) as gas recognition material. From the results of physiological application, the bio-sniffers could monitor the concentration changes in breath ethanol and acetaldehyde after drinking. The ethanol and acetaldehyde concentrations in expired air from ALDH2 [−] (aldehyde dehydrogenase type 2 negative) subjects were higher than that of the ALDH2 [+] (positive) subjects. The results indicated that the lower activity of ALDH2 induced an adverse effect on ethanol metabolism, leading to ethanol and acetaldehyde remaining in the human body, even human expired air.